Gürelli, M. I.Onural, L.2016-02-082016-02-0819940162-8828http://hdl.handle.net/11693/26011This correspondence is about a Gibbs-Markov random field (GMRF) parameter estimation technique proposed by Derin and Elliott. We will refer to this technique as the histogramming (H) method. First, the relation of the H method to the (conditional) maximum likelihood (ML) method is considered. Second, a bias-reduction based modification of the H method is proposed to improve its performance, especially in the case of small amounts of image data.EnglishGibbs-Markov random fieldsImage modelingparameter estimationpattern recognitionTextureImage analysisImage processingParameter estimationStatistical methodsBias reduction based modificationGibbs Markov random fieldsHistogrammingImage modellingMaximum likelihood methodPattern recognitionArticle10.1109/34.277597